def predict_raw(self, net, images):
tta_masks = []
for tta in self.tta:
masks_predictions = net(tta.transform_forward(images))
masks_predictions = tta.transform_backward(masks_predictions)
tta_masks.append(masks_predictions)
tta_masks = torch.stack(tta_masks, dim=1)
return tta_masks
def predict(self, net, images):
tta_masks = []
for tta in self.tta:
masks_predictions = net(tta.transform_forward(images))
masks_predictions = torch.sigmoid(tta.transform_backward(masks_predictions))
tta_masks.append(masks_predictions)
tta_masks = torch.stack(tta_masks, dim=0)
masks_predictions = torch.mean(tta_masks, dim=0)
return masks_predictions
